Emission control devices, such as particulate filters (PF), may reduce the amount of soot emissions from an internal combustion engine by trapping soot particles. Such devices may be passively regenerated during operation of the engine to decrease the amount of trapped particulate matter. Regeneration is typically achieved by raising a temperature of the PF to a predetermined level for a sustained period, while flowing exhaust gas of a defined composition through the PF in order to burn or oxidize the trapped particulate matter. However, during vehicle operation, conditions for sustained full regeneration of the PF may not be available. For example, during urban driving conditions which include frequent idle stops and light load engine operation, frequent premature terminations of regeneration may occur. The premature terminations may result in the need for active regeneration, leading to an increased regeneration fuel penalty.
Various approaches are provided for regenerating a PF during a vehicle drive cycle. In one example, as shown in US20160075333, Sujan et al. disclose a method to compute a recommended route for vehicle travel taking into account the regeneration requirement of an exhaust after-treatment device. Factors that are considered during route computation include load information of the vehicle, traffic information, and a cost strategy. Simulations are carried out to select a preferred route which is then provided to the vehicle operator.
However, the inventors herein have recognized potential disadvantages with the above approach. As one example, in the approach of Sujan et al., when the driver does not provide a destination, it may be difficult to suggest a route of travel that enables sufficient regeneration. Also, during conditions when an operator starts on the recommended route but takes a detour, the resulting route may have a lower regeneration efficiency than was intended. Further, operator driving history, driving characteristics, and driving preferences may significantly affect the decision of the operator to accept the route that is recommended by the vehicle controller. As a result, the PF may remain insufficiently regenerated.
In one example, the issues described above may be addressed by an engine method, comprising: learning, after each drive cycle, a particulate filter regeneration efficiency as a function of one or more characteristics of a travelled route and operator behavior over the travelled route, updating a database based on the learning, and at onset of a drive cycle, displaying to an operator one or more routes selected from the database, the selection based on a particulate filter soot load at the onset of the drive cycle. In this way, by providing route recommendations to a vehicle operator to enable sufficient exhaust after-treatment device regeneration based on operator driving characteristics and history, PF regeneration may be better scheduled.
As one example, a vehicle controller may develop a route database for a vehicle operator as a function of routes that are frequently used, along with operator driving characteristics on each route. Each time a trip is completed, the database may be updated with drive information including origin and destination details, route details such as route terrain, grade, day of week and time of day at which travel occurs, vehicle stops incurred during the route and duration of each stop, traffic information for the route as a function of time of travel, engine operating conditions on route, fuel consumption, duration of travel, possible or actual degree of PF regeneration achieved on traveled route, operator driving characteristics (e.g., aggressiveness and pedal actuation frequency), etc. The different routes may be stored in the database and ranked in terms of one or more parameters such as fuel efficiency, duration of travel, and achievable PF regeneration level. On each drive cycle, the controller may receive input regarding a final destination from the operator (such as via a navigation system). Responsive to the operator input, and further based on the current soot level of the PF, one or more routes may be selected from the database and hierarchically displayed to the vehicle operator.
For example, when the PF soot level is lower than a threshold and PF regeneration is not desired during the upcoming drive cycle, the selected routes that are displayed may be ranked based on the time taken to reach the destination and/or fuel cost, and the recommended route may be selected independent of its ability to complete PF regeneration. Thus, the recommended route at the top of the list may be a route that enables the destination to be reached in the shortest amount of time or using the least amount of fuel. As another example, when the PF soot level is higher than a threshold and PF regeneration is desired during the upcoming drive cycle, the selected routes that are displayed may be first ranked based on their ability to complete PF regeneration. Then routes may be further weighted based on their fuel economy. Thus, the recommended route at the top of the list may be a route that enables the destination to be reached while providing the highest degree of regeneration and while providing some degree of fuel economy. The subsequent route may provide a relatively lower degree of regeneration while still providing some degree of fuel economy, and so on. Navigational instructions may then be provided based on the operator selection. However, if a final destination is not provided by the operator, an expected destination may be predicted based on the operator's drive history (e.g., based on destinations commonly frequented on the given day of the week, and the given time of the day) and a route selection may be provided based on the expected destination. The vehicle controller may divide the route into route segments and predict an expected destination for an initial route segment and provide a recommended route that enables PF regeneration on the initial route segment. Then, as the operator starts driving, the expected destination for one or more subsequent route segments, and a recommended route for each route segment, may be dynamically updated using stochastic dynamic programming. Similarly, when the operator starts on the recommended route and takes a detour, upcoming route segments may be predicted based on the drive history in the database, and one or more routes may be recommended from the database using stochastic dynamic programming.
In this way, by maintaining a database of frequently traveled routes with information including the actual degree of PF regeneration attained on each route, it may be possible to select one or more routes from a database based on PF regeneration requirement during a future drive cycle. By dynamically selecting and suggesting a travel route that enables PF regeneration while taking into account an operator's driving history and the operator's driving preferences, the likelihood that an operator will follow the recommended route is increased. Consequently, a higher degree of PF regeneration may be facilitated without substantial increase in fuel consumption and travel duration. The technical effect of using stochastic dynamic programming to predict segments of an upcoming route based on drive history and drive statistics stored in the route database is that it may be possible to schedule PF regenerations even during trips where a final destination has not been specified by the operator or when the operator has taken a detour from the selected route. In this way, by opportunistically regenerating the PF, over-loading of soot in the PF may be reduced, thereby improving engine performance and PF health.
It should be understood that the summary above is provided to introduce in simplified form a selection of concepts that are further described in the detailed description. It is not meant to identify key or essential features of the claimed subject matter, the scope of which is defined uniquely by the claims that follow the detailed description. Furthermore, the claimed subject matter is not limited to implementations that solve any disadvantages noted above or in any part of this disclosure.